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HDFS-8942. Update hyperlink to rack awareness page in HDFS Architecture documentation. Contributed by Masatake Iwasaki. 

(cherry picked from commit bcaf83902a)
This commit is contained in:
Akira Ajisaka 2015-08-24 13:52:49 +09:00
parent 85363ea4bd
commit f7ee225052
2 changed files with 5 additions and 1 deletions
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hadoop-hdfs-project/hadoop-hdfs/CHANGES.txt
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@ -854,6 +854,9 @@ Release 2.8.0 - UNRELEASED
HDFS-8809. HDFS fsck reports under construction blocks as "CORRUPT". (jing9) HDFS-8809. HDFS fsck reports under construction blocks as "CORRUPT". (jing9)
HDFS-8942. Update hyperlink to rack awareness page in HDFS Architecture
documentation. (Masatake Iwasaki via aajisaka)
Release 2.7.2 - UNRELEASED Release 2.7.2 - UNRELEASED
INCOMPATIBLE CHANGES INCOMPATIBLE CHANGES

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hadoop-hdfs-project/hadoop-hdfs/src/site/markdown/HdfsDesign.md
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@ -116,7 +116,8 @@ The placement of replicas is critical to HDFS reliability and performance. Optim
Large HDFS instances run on a cluster of computers that commonly spread across many racks. Communication between two nodes in different racks has to go through switches. In most cases, network bandwidth between machines in the same rack is greater than network bandwidth between machines in different racks. Large HDFS instances run on a cluster of computers that commonly spread across many racks. Communication between two nodes in different racks has to go through switches. In most cases, network bandwidth between machines in the same rack is greater than network bandwidth between machines in different racks.
The NameNode determines the rack id each DataNode belongs to via the process outlined in [Hadoop Rack Awareness](../hadoop-common/ClusterSetup.html#HadoopRackAwareness). A simple but non-optimal policy is to place replicas on unique racks. This prevents losing data when an entire rack fails and allows use of bandwidth from multiple racks when reading data. This policy evenly distributes replicas in the cluster which makes it easy to balance load on component failure. However, this policy increases the cost of writes because a write needs to transfer blocks to multiple racks. The NameNode determines the rack id each DataNode belongs to via the process outlined in [Hadoop Rack Awareness](../hadoop-common/RackAwareness.html).
A simple but non-optimal policy is to place replicas on unique racks. This prevents losing data when an entire rack fails and allows use of bandwidth from multiple racks when reading data. This policy evenly distributes replicas in the cluster which makes it easy to balance load on component failure. However, this policy increases the cost of writes because a write needs to transfer blocks to multiple racks.
For the common case, when the replication factor is three, HDFS’s placement policy is to put one replica on one node in the local rack, another on a different node in the local rack, and the last on a different node in a different rack. This policy cuts the inter-rack write traffic which generally improves write performance. The chance of rack failure is far less than that of node failure; this policy does not impact data reliability and availability guarantees. However, it does reduce the aggregate network bandwidth used when reading data since a block is placed in only two unique racks rather than three. With this policy, the replicas of a file do not evenly distribute across the racks. One third of replicas are on one node, two thirds of replicas are on one rack, and the other third are evenly distributed across the remaining racks. This policy improves write performance without compromising data reliability or read performance. For the common case, when the replication factor is three, HDFS’s placement policy is to put one replica on one node in the local rack, another on a different node in the local rack, and the last on a different node in a different rack. This policy cuts the inter-rack write traffic which generally improves write performance. The chance of rack failure is far less than that of node failure; this policy does not impact data reliability and availability guarantees. However, it does reduce the aggregate network bandwidth used when reading data since a block is placed in only two unique racks rather than three. With this policy, the replicas of a file do not evenly distribute across the racks. One third of replicas are on one node, two thirds of replicas are on one rack, and the other third are evenly distributed across the remaining racks. This policy improves write performance without compromising data reliability or read performance.